1. Field of the Invention
The present invention relates to an on-board apparatus installed in a mobile object such as an automobile or an electric train and, more specifically, it relates to a device that estimates a position.
2. Description of Related Art
A car navigation system in the related art determines the subject vehicle position through map matching executed based upon positioning results. In a vehicle motion control system in which the vehicle position provided by a car navigation system is output to a vehicle motion control device such as that disclosed in Japanese Laid Open Patent Publication No. 2008-287669, the vehicle position must be measured with a higher level of accuracy.
A technology whereby a plurality of mathematical expression models, to be used for subject vehicle calculation, are prepared and a subject vehicle position calculation is executed by switching from one mathematical expression model to another based upon a specific threshold value determined in advance, has been proposed as a measure for assuring accurate positioning. For instance, Japanese Laid Open Patent Publication No. H8-14923 discloses an apparatus that switches to position calculation via a relative sensor such as a gyro sensor or an acceleration sensor if the error in the position signal output from a global positioning system (GPS) is equal to or greater than a specific extent, based upon information indicating the GPS signal strength, the satellite positions and the like.
Systems that estimate the subject vehicle position by using a probability system such as the Kalman filter probability model include an apparatus disclosed in Japanese Laid Open Patent Publication No. H5-333132. The approach measures the subject vehicle position by switching from one Kalman filter to another among a plurality of Kalman filters prepared in advance in a quantity corresponding to the number of GPS satellites from which signals can be received. The technologies for estimating the subject vehicle position by using a position estimation logic based upon a probability model such as a Kalman filter probability model or a particle filter probability model, include the technology disclosed in Japanese Laid Open Patent Publication No. 2007-322391, which estimates the subject vehicle position based upon an extended Kalman filter algorithm.
Positioning error models used in the known art used in a car navigation system that switches position calculation methods based upon the positioning error and is equipped with a steering angle sensor and a gyro sensor, include the speed-based Ackermann model and dead-reckoning models. In a car navigation system equipped with a GPS and a gyro sensor in the known art, a sensor fusion model may be used when the GPS is used and a dead-reckoning model may be used if no GPS signals are received or the GPS is not used.
The Ackermann model is described in “Automotive Vehicle Dynamics” by Masato Abe, published by Tokyo Denki University Press, March, 2008, ISBN: 9784501417000. The sensor fusion model and an internal sensor model are described in “Positioning of a Vehicle on Undulating Ground Using GPS and Internal Sensors” by Toshihiro Aono et. al in the Collection of Research Papers, Vol. 35, No. 8, 1999, published by the Society of Instrument Control Engineers.
As described in Japanese Laid Open Patent Publication No. 2008-26282, disclosing a mathematical expression model that allows links in digital map data to be utilized in a Kalman filter observation equation, the subject vehicle position may be set on a digital map through map matching in conjunction with a sensor fusion model (hereafter referred to as a “link fusion model”) so as to enable map matching operation based upon the link information included in the digital map information.